In the area of smart cities, great emphasis is placed on many different fields such as energetics, information systems, and transportation. All of these should lead to a simplification of life thanks to smart technologies. If we talk about the transportation field, the main issues related to this area are safety, traffic efficiency, or the environment. Another condition is the successful acceptance of any new technology by its users. Cooperative systems prove to be a suitable solution for these issues, especially in urban areas. Today, pilot implementations of cooperative systems in European countries are being carried out. However, before they are put into full operation, they need to be tested, evaluated, and assessed. This article focuses on the latter two points, i.e., evaluation and assessment of the cooperative systems. For this purpose, a methodology was created, which describes the procedure chosen in the evaluation and assessment of cooperative systems in the Czech Republic and a demonstration of its use by example. The methodology is focused on three main areas, which in this case are functional evaluation, user acceptance, and impact assessment. For the area of user acceptance, the main source was questionnaires, impact assessment relied on measured data while functional evaluation was based on discussions with the drivers, evaluating the cooperative systems, the measured data, and the expert observations. All collected and measured data were then processed and some of the results of the evaluation of the selected service are presented at the end of this article.

The article presents a novel algorithm for merging Bayesian networks generated by different methods, such as expert knowledge and data-driven approaches, while leveraging a symmetry-based approach. The algorithm combines the strengths of each input network to create a more comprehensive and accurate network. Evaluations on traffic accident data from Prague in the Czech Republic and accidents on railway crossings demonstrate superior predictive performance, as measured by prediction error metric. The algorithm identifies and incorporates symmetric nodes into the final network, ensuring consistent representations across different methods. The merged network, incorporating nodes selected from both the expert and algorithm networks, provides a more comprehensive and accurate representation of the relationships among variables in the dataset. Future research could focus on extending the algorithm to deal with cycles and improving the handling of conditional probability tables. Overall, the proposed algorithm demonstrates the effectiveness of combining different sources of knowledge in Bayesian network modeling.

In recent years, the concept of smart cities, along with autonomous transportation, has emerged as a significant focal point for researchers, urban planners, and technological innovators. This growing interest is driven not only by technological advancements but also by the pressing need to address current urban mobility challenges such as congestion, air pollution, and the necessity to enhance road safety. Autonomous trams, as a pivotal element of intelligent urban transportation systems, offer a promising pathway towards more efficient, safer, and sustainable urban mobility. With their ability to integrate with a wide range of technologies, from advanced traffic management systems to sensors and artificial intelligence, autonomous trams represent a revolutionary step towards achieving smooth and secure movement in urbanized areas. However, the development and integration of autonomous trams into urban transport systems require not only advanced technologies but also comprehensive testing and validation of their communication with urban infrastructure and the functions of relevant devices. HD maps and digital twins play a crucial role in this process, enabling precise navigation and interaction with the urban environment. These technologies not only enhance the efficiency and safety of autonomous trams but also contribute to a better understanding and management of the urban space. This article focuses on the significance of comprehensive testing of the communication between autonomous trams and urban infrastructure, as well as the functionality of relevant devices, with an emphasis on the use of HD maps and digital twins. Highlighting the theoretical framework and methodologies that are essential for conducting such tests, the paper discusses the anticipated approach and potential challenges. By addressing the broader implications for the development of intelligent urban transportation systems, the article aims to shed light on how these technologies can help overcome the current and future challenges of urban mobility.

In the field of Cooperative Intelligent Transport Systems (C-ITSs), the traditional approach to testing often emphasizes technological parameters, leaving the validation of message content insufficiently addressed. Since the content of these messages is crucial for the correct functioning of C-ITS, this article demonstrates the potential for automated evaluation of C-ITS message content against relevant standards. It leverages our novel tools, Karlos and C-ITS SIM, to facilitate this process. Through detailed laboratory testing and data analysis, the study showcases the effectiveness of these automated solutions in enhancing the accuracy and reliability of message content validation.

The volume of data streams in different areas of the smart city concept, e.g. robust IT connectivity or efficient urban mobility, has been ballooning in recent times, and yet, the issue of how to protect this data is remaining on the margin of attention. Several possible approaches may be taken to data protection, which arise from different perspectives. The most well-known of these is the much-mentioned General Data Protection Regulation, dealing with the protection of personal data. Data is generally stored in a space called a database, i.e., a tool for collecting and organizing data. As far as databases are concerned, there is a separate approach to their protection which may be directly associated with the design of the database and/or its contents. The purpose of this article is to provide the reader with insight into this issue with respect to specific databases within the field of autonomous mobility. In addition, this article includes a proposal as to what characteristics selected databases should have that affect their possible protection, and the conclusions to be derived from this.